Smart Traffic Management Systems: A Machine Learning Approach

The increasing number of vehicles around the world has led to a widespread problem of traffic congestion, wasting valuable time at major intersections. Traditional traffic management systems work well under low traffic conditions but struggle when vehicle density varies across different lanes. To tackle this issue, we propose transitioning from a static to a dynamic signal switching model in traffic control systems. This novel approach seeks to overhaul the conventional traffic management framework, providing more efficient control during fluctuating traffic volumes, and creating a more adaptive and intelligent system for managing road traffic.